Flow diverters failing to occlude experimental bifurcation or curved sidewall aneurysms: an in vivo study in canines
Bibliographic record
Abstract
OBJECT: Flow diverters (FDs) are increasingly used to treat complex intracranial aneurysms, but preclinical studies that could guide clinical applications are lacking. The authors designed a modular aneurysm model in canines to address this problem. METHODS: Three variants of one modular aneurysm model were constructed in 21 animals. Sidewall (n=5), curved sidewall (n=5), and end-wall bifurcation (n=7) aneurysms were treated with prototype 36-wire FDs. Four more end-wall bifurcation aneurysms were treated with prototype 48-wire lower-porosity FDs. Angiographic results postimplantation and at 3 months were scored with an ordinal scale. Animals were euthanized at 3 (n=17) or 6 (n=3) months, and the FD covering the aneurysm ostium was photographed to analyze metallic porosity and amount of neointima formation. RESULTS: Straight sidewall aneurysms were better occluded than curved sidewall and end-wall bifurcation aneurysms at the 3-month angiography follow-up (p=0.010). Flow diverters failed to occlude curved sidewall aneurysms (n=0/5) and all but one (n=1/7) end-wall bifurcation aneurysm. Angiographic results were no better (n=0/4) using a 48-wire FD (p=0.788). Branches jailed by the FD (n=16) remained patent in all cases. Metallic porosity was decreased (p=0.014) and neointimal closure of the aneurysm ostium was more complete (p=0.040) in sidewall aneurysms than in curved or bifurcation variants of the model. CONCLUSIONS: Flow diverters may succeed in treating straight sidewall aneurysms, but the same device repeatedly fails to occlude curved sidewall and end-wall bifurcation aneurysms. In vivo studies can be designed to test basic principles that, once validated, may serve to guide clinical use of new devices.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".